Distributionexample use case
Reporting automation: a management report that builds itself
Every Friday, or at month end, someone downloads exports from the ERP, accounting, the online shop and the CRM, pastes them into Excel, checks them and writes a commentary for management. Reporting automation turns that into a report that is ready on Monday morning on its own — with a note on what changed and what deserves a closer look. To be straight with you: a well-configured BI tool solves much of this without any AI. We add AI where it genuinely helps.
Sound familiar?
- A controller or management assistant spends half a day to a full day every week downloading exports and stitching spreadsheets together.
- Figures from the ERP, accounting and the online shop do not match, and every report starts with hunting for the difference.
- Exactly one person knows how the report is calculated. When they are on holiday, there is no report.
- Management gets a table but not the answer to “why” — and a follow-up question waits until next week.
How it works
1. Data is pulled from the sources automatically
We connect the ERP, accounting, online shop and CRM via API, database or a scheduled export. Every night the data lands in one place, with customer, product and cost-centre codes reconciled.
2. The report builds itself
The calculations someone does by hand in Excel today are written down once and for all. At a set time the report is generated as a Power BI or Looker Studio dashboard, or as the familiar Excel file management receives by email.
3. AI drafts the commentary and flags anomalies
On top of the finished figures, AI writes a short commentary: what changed against last week and the plan, where the variances are and what to look at. Unusual swings — a branch’s sales dropping off, a sudden rise in credit notes — are sent straight away rather than waiting for the report.
4. Management asks in plain language
Ask “why did the margin drop in the east region?” in Teams or by email. The system answers from the same data as the report and shows which calculation the answer came from.
What the system handles
- ERP and accounting systems — typically Pohoda, Money, Helios, SAP Business One or a custom system — via API, database or scheduled export.
- Online shops (Shoptet, WooCommerce, Shopify), CRMs (Pipedrive, HubSpot, Raynet) and Google Analytics.
- Spreadsheets that departments keep by hand, and unstructured sources too: sales notes, emails, PDF statements.
- Weekly, monthly and per-branch reports compared against plan and the previous period.
- Delivered where management reads it: a Monday-morning email, Teams, Slack or a dashboard.
Human oversight and safety
- The database calculates the figures, not the language model. AI only comments on finished results, and every number in the commentary is automatically checked against the source.
- For the first few weeks the automated report runs alongside the manual one — nothing is switched off until the figures match.
- For plain-language questions you see which data and which calculation produced the answer. The system has read-only access to the data.
- The calculation rules are written down and documented — the report no longer depends on one person.
What result is realistic
~10 h
saved on reporting every week
For a typical distribution company with a weekly management report and monthly branch reports, we plan for around 10 hours a week saved on downloading, stitching and checking. The report is ready on Monday morning instead of Wednesday, and management’s follow-up questions no longer wait a week. If an automated report without AI commentary is enough, the solution costs less and pays back sooner — and we will tell you that at the start.
The figures are indicative for typical volumes. We give a precise estimate for your company after analysing the process.
Indicative scope
- Analysis of reports and data sources
- €900 – €1,800
- Automated report from 2–3 sources (3–5 weeks)
- €3,000 – €6,000
- AI commentary, variance alerts and questions on the data
- €4,000 – €10,000
- Operations and monitoring
- from €290 / month
Prices are indicative and exclude VAT. We give an exact figure only after analysing your process — not off the cuff on the first call.
Frequently asked questions
Would Power BI or Looker Studio not be enough?
Often, yes. If the data is in order and the sources have an interface, a well-configured BI tool will build an automated report without AI — and in that case that is what we will recommend. AI adds value in the commentary for management, with unstructured sources and for plain-language questions about the data.
Will the AI make up numbers?
It does not calculate them. The database does the maths according to written-down rules; AI receives the finished results and writes a commentary on them. Every number in the commentary is automatically checked against the source, and a mismatch never reaches the report.
What if our system has no API?
A scheduled export to a folder or access to the database is enough. Older systems can be connected too — it just takes more work, and we will tell you so up front.
Do we have to clean up our data first?
Partly. Automation will not fix mismatched customer or product codes between systems — it will only expose them. We set up the mapping tables as part of the project and show the biggest inconsistencies during the analysis.
How long until the report runs on its own?
The first automated report from 2–3 sources usually takes 3–5 weeks. We add AI commentary and questions on the data only once the figures match the manual report.
Related service
Connecting AI to your systems
We build this solution as part of our service „Connecting AI to your systems“.
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You do not need to know whether you need AI, automation or a new system. Show us the process that slows you down — we will tell you what can be automated and whether it pays off.